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Tactical fleet mix computation using multiobjective evolutionary optimization

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3 Author(s)
Stuive, L. ; Canadian Forces Aerosp. Warfare Centre OR Team, Ottawa, ON, Canada ; Wesolkowski, S. ; Ghanmi, A.

A multi-objective model for determining optimal fleet mixes for a set of non-concurrent tactical missions is studied. An implementation of the multiobjective evolutionary algorithm (MEA) NSGA-II is used to solve the problem, and it is compared to an exhaustive search of the fleet mix space as well as a solution set obtained by a Mixed Integer Non-Linear Program. The exhaustive and MEA searches are compared with respect to both accuracy and computational complexity. The use of an alternative genotypic representation is investigated; its slow convergence is used to demonstrate the importance of chromosome choice, aligning with past research on locality and redundancy in genotypic representations.

Published in:

Evolutionary Computation (CEC), 2010 IEEE Congress on

Date of Conference:

18-23 July 2010